SIGFinger: A subtle and interactive GNN fingerprinting scheme via spatial structure inference perturbation

Publication Type

Journal Article

Publication Date

7-2025

Abstract

There have been significant improvements in intellectual property (IP) protection for deep learning models trained on euclidean data. However, the complex and irregular graph-structured data in non-euclidean space poses a huge challenge to the IP protection of graph neural networks (GNNs). To address this issue, we propose a subtle and interactive GNN fingerprinting scheme through spatial structure inference perturbation, which captures the stable coordination patterns of fingerprint to guarantee the reliability of copyright verification. Specifically, the data augmentation based on adaptive graph diffusion is first exploited to generate more samples, which enables the exploration of fingerprint information from coarse to fine. Subsequently, the graph-structured data are manipulated by multi-constrained spectral clustering to analyze intrinsic and extrinsic structure correlations in a causal inference manner. Ultimately, the cycle-consistent statistical optimization is performed to determine the copyright of GNN models from both intra-graph and inter-graph perspectives. Extensive experiments show that our proposed scheme can effectively verify the IP of GNN models on various challenging graph-structured datasets. Furthermore, we reveal that the space causality inference can facilitate the acquisition of inherent structural information, which improves the quality and robustness of the fingerprint under model modification operations and other model stealing attacks.

Keywords

IP protection, GNN fingerprinting, causal inference, stable structure knowledge, quality and robustness.

Discipline

Information Security

Research Areas

Information Systems and Management

Publication

IEEE Transactions on Dependable and Secure Computing

Volume

22

Issue

4

First Page

3629

Last Page

3646

ISSN

1545-5971

Identifier

10.1109/TDSC.2025.3535588

Publisher

Institute of Electrical and Electronics Engineers

Additional URL

https://doi.org/10.1109/TDSC.2025.3535588

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